Evaluating the Application of Large Language Models to Generate Feedback in Programming Education

Autor:	Jacobs, Sven, Jaschke, Steffen
Rok vydání:	2024
Předmět:	Computer Science - Computation and Language Computer Science - Artificial Intelligence Computer Science - Computers and Society Computer Science - Human-Computer Interaction
Druh dokumentu:	Working Paper
DOI:	10.1109/EDUCON60312.2024.10578838
Popis:	This study investigates the application of large language models, specifically GPT-4, to enhance programming education. The research outlines the design of a web application that uses GPT-4 to provide feedback on programming tasks, without giving away the solution. A web application for working on programming tasks was developed for the study and evaluated with 51 students over the course of one semester. The results show that most of the feedback generated by GPT-4 effectively addressed code errors. However, challenges with incorrect suggestions and hallucinated issues indicate the need for further improvements. Comment: accepted at IEEE Global Engineering Education Conference 2024, Kos, Greece
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2403.09744 Zobrazit plný text záznamu View this record from Arxiv